SyMbolic

Systemic Models for Metabolic Dynamics and Regulation of Gene Expression

Keywords: bioinformatics, gene expression, metabolism, data-based modeling, latent variable models, regulatory interactions

The development of measurement techniques in bioinformatics has lead to increasing amounts of available data. However, the accurate modeling tools are missing, mostly because the processes are complex and high-dimensional.

The aim of this research is to develop data-based model structures to describe cell behaviour and gene interactions more accurately. The results are to be used to increase the knowledge of the operation of biological systems. Especially, the focus is on how the cells react to sudden environmental changes or the suppression of some particular genes. The results may be further exploited e.g. in cell modifications for enzyme production

Publications

• Olli Haavisto and Heikki Hyötyniemi,
  "Multivariate regression applied to gene expression dynamics,"
  in Computational Intelligence in Bioinformatics, Arpad Kelemen, Ajith Abraham and Yuehui Chen (eds.), Berlin Heidelberg: Springer-Verlag, 2008, pp. 257-275.
• Olli Haavisto, Heikki Hyötyniemi and Christophe Roos,
  "State space modeling of yeast gene expression dynamics,"
  Journal of Bioinformatics and Computational Biology, Vol. 5, no. 1, pp. 31-46, 2007.
  Electronic publication
• Olli Haavisto and Heikki Hyötyniemi,
  "Neocybernetic modeling of a biological cell,"
  in Proceedings of the Ninth Scandinavian Conference on Artificial Intelligence (SCAI 2006), Timo Honkela, Tapani Raiko, Jukka Kortela and Harri Valpola (eds.), Espoo, Finland: Finnish Artificial Intelligence Society, 2006, pp. 209-216.